Dqc-toolkit

Latest version: v0.1.3

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0.1.3

What's Changed

Update`pyproject.toml` to resolve dependency issues
- Change version constraint for scikit-learn from **`>=1.3.2`** to **`>=1.3.2,<1.5`**

0.1.2

What's Changed
* Fix datatype mismatch between input labels and `predicted_label` returned by `CrossValCurate.fit_transform` in (https://github.com/sumanthprabhu/DQC-Toolkit/pull/9)

0.1.1

What's Changed
* Add issue templates for bug reports and feature requests
* Fix for spurious column issue with `CrossValCurate.fit_transform` (https://github.com/sumanthprabhu/DQC-Toolkit/pull/7)

0.1.0

What's changed
* Improved `calibration_using_baseline` performance by replacing `minmax` based rescaling with unit norm normalization (https://github.com/sumanthprabhu/DQC-Toolkit/pull/1)
* Added multiple version support in documentation (https://github.com/sumanthprabhu/DQC-Toolkit/pull/2)

0.1.0rc1

- Added CrossValCurate to curate noisy text classification datasets with support for
- TfidfVectorizer, CountVectorizer and SentenceTransformer objects as feature extractors
- Sklearn classifiers which implement 'predict_proba' method as curation model
- Calibration of prediction probabilities of curation model
- Added Util functions to
- Simulate noisy labels in text classification
- Fetch information to assist debugging
- Added corresponding tests and documentation

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